Hybrid heuristic for the location‐inventory‐routing problem in closed‐loop supply chain

This study examines a location‐inventory‐routing problem in a closed‐loop supply chain (LIRP‐CL) that considers random demands, as well as random returns, from customers. In reality, some of the returned products can be remanufactured as new products, and they share the same channel with new products. This practice renders previous models no longer appropriate. We consider this practice in this paper and build a new LIRP‐CL system. To minimize the total costs of the system, this paper determines the locations of distribution centers and remanufacturing centers, the inventory level of the system, and the delivery routes from distribution centers to customers and from customers to remanufacturing centers. A mixed integer nonlinear model was developed to solve this problem. To solve the model, a novel hybrid heuristic algorithm based on tabu search and simulated annealing is proposed. The computational results and sensitivity analysis are presented. In addition, some managerial insights are proposed.